Research on Themes of Social Media User Comments: Sentiment Analysis Based on DingTalk App Reviews

This study aims to explore users’ emotional changes and main concerns in different contexts through quantitative and qualitative analysis of Nail App user comments. The LDA theme model is used to analyze the comment data, and the results show that the positive comments mainly focus on the functional advantages of the platform, especially in distance education and team collaboration, while the negative comments focus on technical stability and user privacy protection issues. With the expansion of the user base and the continuous optimization of the functions, the comment themes gradually diversified, and the negative sentiment reached its peak during the outbreak, especially the online education function, which triggered widespread dissatisfaction. With the later improvements of the platform, the positive feedback gradually increased, indicating that users recognized the improvements of Nail. This study provides an empirical basis for understanding user sentiment and its changes, and provides a reference for future product optimization and user experience enhancement. Companies should emphasize technical stability and privacy protection to further enhance user satisfaction and promote the sustainable development of the platform.

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Publication Details

Published
2024-11-21
DOI
https://doi.org/10.1109/iciibms62405.2024.10792691
Citations
1
Primary Topic
Sentiment Analysis and Opinion Mining
Type
article
Field-Weighted Citation Impact
0.35
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article

Research on Themes of Social Media User Comments: Sentiment Analysis Based on DingTalk App Reviews

Yuqin Shen
1 citations
Sentiment Analysis and Opinion Mining
0.35
article

Research on Themes of Social Media User Comments: Sentiment Analysis Based on DingTalk App Reviews

Yuqin Shen
article en
1 citations

Abstract

This study aims to explore users’ emotional changes and main concerns in different contexts through quantitative and qualitative analysis of Nail App user comments. The LDA theme model is used to analyze the comment data, and the results show that the positive comments mainly focus on the functional advantages of the platform, especially in distance education and team collaboration, while the negative comments focus on technical stability and user privacy protection issues. With the expansion of the user base and the continuous optimization of the functions, the comment themes gradually diversified, and the negative sentiment reached its peak during the outbreak, especially the online education function, which triggered widespread dissatisfaction. With the later improvements of the platform, the positive feedback gradually increased, indicating that users recognized the improvements of Nail. This study provides an empirical basis for understanding user sentiment and its changes, and provides a reference for future product optimization and user experience enhancement. Companies should emphasize technical stability and privacy protection to further enhance user satisfaction and promote the sustainable development of the platform.

Shanghai Institute of Technology (CN)
Openalex Percentile: Top 31%
Sentiment Analysis and Opinion Mining
0.35
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